Functional tumor imaging like dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can be used to obtain biological information about the cancer disease and thereby assess tumor aggressiveness. It has thus been proposed that these imaging techniques (DCE-MRI) may be useful tools in the clinic to stratify patients to different treatment regimes on the way to personalized therapy. In particular, patients treated with radiotherapy may benefit considerable from such an approach, due to the central role of imaging in the radiotherapy planning (1). A powerful strategy for future improvements in radiotherapy could be to link the discovery of molecular biomarkers of radioresistance to developments in functional imaging techniques (Coleman). PET and MRI are now indispensable tools in the handling of cancer patients to detect metastases and assess disease dissemination. However, their ability to visualize tumor biology and aggressiveness has not been utilized, mainly because it is not yet clear how to best extract the prognostic parameters nor their biological meaning from the images.
Several studies have recently demonstrated the potential in combining imaging data with gene expression data of the same tumors, to find valuable information about the background of various imaging parameters (15-21). However, there is still unexplored information embedded in the images which needs to be elucidated to be able to efficiently use DCE-MRI as a biomarker in cervical cancer.